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This paper distinguishes between bridging and bonding social capital to assess their roles for individual farmers’ adaptation strategies taken through technology adoption. Based on primary data collected in Langcang River (LCR) basin area in southwestern China, the paper finds: (1) adaptation measures have been widely taken by surveyed households, but non-infrastructure-based measures are more prevalent than infrastructure-based measures and (2) surveyed households have strong social capital while having weak bridging social capital. Their bonding social capital has significantly positive relationship with their adaptation decisions, but bridging social capital does not have such statistically significant relationship. It recommends that the governments contemplate carefully how to help the poor to get a good combination of bonding and bridging social capital when designing policies to help the rural poor to improve their long-term adaptive capacity and achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Climate change is a potential threat to achieving food security, particularly in the most food insecure regions. However, interpreting climate change projections to better understand the potential impacts of a changing climate on food security outcomes is challenging. This paper addresses this challenge through presenting a framework that enables rapid country-level assessment of vulnerability to food insecurity under a range of climate change and adaptation investment scenarios. The results show that vulnerability to food insecurity is projected to increase under all emissions scenarios, and the geographic distribution of vulnerability is similar to that of the present-day; parts of sub-Saharan Africa and South Asia are most severely affected. High levels of adaptation act to off-set these increases; however, only the scenario with the highest level of mitigation combined with high levels of adaptation shows improvements in vulnerability compared to the present-day. The results highlight the dual requirement for mitigation and adaptation to avoid the worst impacts of climate change and to make gains in tackling food insecurity. The approach is an update to the existing Hunger and Climate Vulnerability Index methodology to enable future projections, and the framework presented allows rapid updates to the results as and when new information becomes available, such as updated country-level yield data or climate model output. This approach provides a framework for assessing policy-relevant human food security outcomes for use in long-term climate change and food security planning; the results have been made available on an interactive website for policymakers (www.metoffice.gov.uk/food-insecurity-index). [ABSTRACT FROM AUTHOR]

This paper investigates the role of intra-regional trade on food availability within the context of global climatic change in the Economic Community of West African States (ECOWAS). To that end, the study uses a module of trade cost minimization built within a bio-economic optimization model of cropland allocation. The results show that the climate-induced trade pattern in ECOWAS depends on the prevailing socio-economic conditions during the century. No specific pattern of trade flows is predicted but several countries may become dependent on food imports outside of ECOWAS. An adjustment of the common external tariffs (CET) may reduce food import costs. Also, doubling crop yields by 2050 could significantly reduce outside dependence. Finally, actions are urgently needed to be taken to foster agricultural production in ECOWAS. [ABSTRACT FROM AUTHOR]

Climate change and variability threaten the sustainability of agricultural and food production, especially in agrarian communities. In Southern Africa, rainfall is expected to decline by almost 10% by the year 2050 and the largest increase in temperature can be experienced. Despite the potential risks of climate change on agricultural productivity, Botswana does not have a dedicated policy to respond to climate change. Furthermore, there is a dearth of research done in Botswana to provide an understanding of factors that shape farmers' adaptation to climate change and institutional link to the adaptive capacity of farming households. Therefore, the aim of this article is to analyse institutions that influence farmers' adaptation strategies of farmers in Botswana, using Ngamiland East as a case study. The paper relies on empirical data collected from purposively selected key informants and 300 households. The results show that the majority of farmers who have climate variability adaptation strategies in place are largely influenced by indigenous knowledge. Women and low-income earners are less likely to employ climate change adaptation strategies in order to improve their agricultural productivity. This article gives a better perspective of the strengths, weaknesses, opportunities and threats facing institutions designed to enable agricultural productivity. It recommends that macro-level and local government institutions should acknowledge the indigenous knowledge, community-level institutions and farmers' adaptive capacity in policy formulation processes. [ABSTRACT FROM AUTHOR]

Total factor productivity (TFP) analysis has been the focus of a large number of methodological and empirical studies over the past several decades. One remarkable gap in this literature is the omission of climatic variables as regressors in the models used to derive TFP measures. The purpose of this paper is to narrow this gap by developing climate-adjusted (CA) TFP measures. We combine information from the Climatic Research Unit with Food and Agriculture Organization data for 28 Latin American and Caribbean countries over a 52-year period (1961-2012) to estimate random parameter stochastic production frontier (SPF) models. The goal is to investigate the impact of climatic variability on TFP. The estimated coefficients from the SPF models are used to construct a climatic effects index across countries and over time. The average annual variation in climatic conditions is stronger at the end of the 2000s compared to earlier periods. Climatic variability has a negative effect on production in 20 of the 28 LAC countries analyzed, and this is more severe over Central America and the Caribbean. The average reduction in output across the region attributable to climatic variables is between 0.02 and 22.7% over the last decade compared to the period 1961-1999. The estimated average annual growth rate of CATFP (0.69%) is consistently lower than TFP (1.08%), confirming the adverse impact of climatic variability on agricultural output and productivity in LAC. The results show considerable variability across countries, and this points to the importance of accounting for climatic effects in analyzing TFP. [ABSTRACT FROM AUTHOR]

Developing appropriate climate change adaptations to protect biodiversity requires taking into account the dynamics of agro-ecological and socio-economic change. A framework for approaching this problem was proposed, but not applied in detail, as part of a major biodiversity and climate change report prepared in Australia. This paper describes the first trial application of the method. It was applied across Vietnam as the Government is interested in identifying adaptation options and detailed data are readily available for its 65 provinces. The process involves identifying ecoregions and collating information for each region based on the current conditions and trends in biodiversity, population, income and agricultural production. Climate change scenarios are identified for each region, together with governance options. Educational needs and key adaptation actions are then identified for each region taking into account the agro-ecological and socio-economic input data. It is concluded that the framework could easily be applied in other countries and should assist the development of strategic adaptation options. [ABSTRACT FROM AUTHOR]

This paper measures the influence of climate normals (average long-term surface wetness and temperature) and interannual climate variance on farms in the United States and Brazil using satellite data. The paper finds that just climate normals or just climate variance variables can explain both net revenues and how much land is used for cropland. However, because they are correlated with each other, it is important to include both normals and variance in the same statistical model to get accurate measures of their individual contribution to farm outcomes. In general, higher climate variance increases the probability that land is used for cropland in both countries and higher temperatures reduce both cropland and land values. Other annual effects were not consistent across the two countries. [ABSTRACT FROM AUTHOR]

Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts of climate change on US returns to research investments on agricultural productivity. We examine this using a historical data set in a panel time-series econometric model of state agricultural productivity. The fitted model allows derivation of the rate of return to research investments and the effects of climate change thereon. We find climate change is altering the rate of return to public agricultural research in a spatially heterogeneous manner. Increases in precipitation raise returns to research, while the impact of higher temperatures varies by region, are negative in Southern areas, particularly the Southern Plains, and positive in northern areas. We simulate the impact of projected climate change and find cases where agricultural productivity is reduced, for example in the Southern Plains. Finally, we consider the amount of research investment that is needed to adapt to overcome the impacts of climate change on agricultural productivity. Under the 2100 scenario, a 7-17 % increase in total US research investment is needed to adapt, but effects by region differ greatly-some requiring little changes and the Southern Plain requiring an increase as high as 57 %. [ABSTRACT FROM AUTHOR]

In the North China Plain, the grain yield of irrigated wheat-maize cropping system has been steadily increasing in the past decades under a significant warming climate. This paper combined regional and field data with modeling to analyze the changes in the climate in the last 40 years, and to investigate the influence of changes in crop varieties and management options to crop yield. In particular, we examined the impact of a planned adaptation strategy to climate change -'Double-Delay' technology, i.e., delay both the sowing time of wheat and the harvesting time of maize, on both wheat and maize yield. The results show that improved crop varieties and management options not only compensated some negative impact of reduced crop growth period on crop yield due to the increase in temperature, they have contributed significantly to crop yield increase. The increase in temperature before over-wintering stage enabled late sowing of winter wheat and late harvesting of maize, leading to overall 4-6% increase in total grain yield of the wheat-maize system. Increased use of farming machines and minimum tillage technology also shortened the time for field preparation from harvest time of summer maize to sowing time of winter wheat, which facilitated the later harvest of summer maize. [ABSTRACT FROM AUTHOR]

This paper examines the effects of climatic and non-climatic factors on the mean and variance of corn, soybean and winter wheat yield in southwestern Ontario, Canada over a period of 26 years. Average crop yields increase at a decreasing rate with the quantity of inputs used, and decrease with the area planted to the crop. Climate variables have a major impact on mean yield with the length of the growing season being the primary determinant across all three crops. Increases in the variability of temperature and precipitation decrease mean yield and increase its variance. Yield variance is poorly explained by both seasonal and monthly climate variable models. Projections of future climate change suggest that average crop yield will increase with warmer temperatures and a longer growing season which is only partially offset by forecast increases in the variability of temperature and rainfall. The projections would also depend on future technological developments, which have generated significant increases in yield over time despite changing annual weather conditions. [ABSTRACT FROM AUTHOR]

The great human-environmental diversity of Mexico provides a framework for an initial understanding of the wide disparities between rich and poor. Mexico is still dominated in many regions by agriculture, and during the last 25 years, weather-related disasters have accounted for about 80% of economic losses. This is dramatic, especially considering that this sector produces only ca. 4% of GDP while providing a livelihood to one-quarter of the country’s population. Based on a spatial model, this paper tests the contribution of natural disasters to catalyzing the emigration process in vulnerable regions throughout Mexico. Besides coping and adaptive capacity, we assess the effect of economic losses from disasters in combination with adverse production and trade conditions during the 1990s in triggering out-migration. [ABSTRACT FROM AUTHOR]

During the recent decade, with the growing recognition of the possibility of climate change and clear evidence of observed changes in climate during 20th century, an increasing emphasis on food security and its regional impacts has come to forefront of the scientific community. In recent times, the crop simulation models have been used extensively to study the impact of climate change on agricultural production and food security. The output provided by the simulation models can be used to make appropriate crop management decisions and to provide farmers and others with alternative options for their farming system. It is expected that in the coming decades with the increased use of computers, the use of simulation models by farmers and professionals as well as policy and decision makers will increase. In India, substantial work has been done in last decade aimed at understanding the nature and magnitude of change in yield of different crops due to projected climate change. This paper presents an overview of the state of the knowledge of possible effect of the climate variability and change on food grain production in India. [ABSTRACT FROM AUTHOR]

Agricultural sectors play a key role in the economics of climate change. Land as an input to agricultural production is one of the most important links between economy and the biosphere, representing a direct projection of human action on the natural environment. Agricultural management practices and cropping patterns exert an enormous effect on biogeochemical cycles, freshwater availability and soil quality. Agriculture also plays an important role in emitting and storing greenhouse gases. To consistently investigate climate policy and future pathways for the economic and natural environment, a realistic representation of agricultural land use is essential. Top-down Computable General Equilibrium (CGE) models have increasingly been used for this purpose. CGE models simulate the simultaneous equilibrium in a set of interdependent markets, and are especially suited to analyze agricultural markets from a global perspective. However, modeling agricultural sectors in CGE models is not a trivial task, mainly because of differences in temporal and geographic aggregation scales. This study surveys some proposed modeling strategies and highlights different tradeoffs involved in the various approaches. Coupling of top-down and bottom-up models is found to be the most applicable for comprehensive analysis of agriculture in prism of climate change. However, linking interdisciplinary data, methods and outputs is still the major obstacle to be solved for wide-scale implementation. [ABSTRACT FROM AUTHOR]

A distinctive feature of Earth’s sedimentary systems is that they all involve the interaction between a nearly-horizontal “equilibrium line,” controlling mass supply, and a dynamic sedimentary surface. For glacial systems, this is the snow line or firn line, approximating a zero-degree atmospheric isotherm. For sedimentary basin systems it is sea level or baselevel. For deep ocean carbonate sediments it is the calcite compensation depth or lysocline. First-order considerations in each case suggest a positive feedback on mass supply as the surface builds upwards (and negative feedback if the surface drops). In the first two cases, outstanding paleo-climate problems exist wherein recorded past sedimentary cycles have asymmetric amplitudes that appear too large compared to deduced vertical movements of the respective equilibrium lines. These problems are familiarly known as the “100-kiloyear Pleistocene ice age cycle” and the “million year high-order Cretaceous relative sea level cycles.” Here, I discuss the emerging commonalities that surround these two amplified cycles, emphasizing the ubiquitous presence of a relative equilibrium line dynamic, and which for glacial systems has long been seen as providing a mass supply feedback that can reconcile the disparity between the forcing and the response. I suggest that, in the same way that continental ice sheets have been modeled as passive sedimentary systems that can freely oscillate with little or no snowline forcing, sedimentary basin systems may be capable of similar behavior without vertical sea level change and illustrate the concepts with a low-order model. Sedimentary indicators for relative sea level change may be displaying disproportionately large responses to small eustatic sea level changes, due to internal positive feedbacks. [ABSTRACT FROM AUTHOR]

Climate change affects all segments of the agricultural enterprise, and there is mounting evidence that the continuing warming trend with shifting seasonality and intensity in precipitation will increase the vulnerability of agricultural systems. Agricultural is a complex system within the USA encompassing a large number of crops and livestock systems, and development of indicators to provide a signal of the impact of climate change on these different systems would be beneficial to the development of strategies for effective adaptation practices. A series of indicators were assembled to determine their potential for assessing agricultural response to climate change in the near term and long term and those with immediate capability of being implemented and those requiring more development. The available literature reveals indicators on livestock related to heat stress, soil erosion related to changes in precipitation, soil carbon changes in response to increasing carbon dioxide and soil management practices, economic response to climate change in agricultural production, and crop progress and productivity. Crop progress and productivity changes are readily observed data with a historical record for some crops extending back to the mid-1800s. This length of historical record coupled with the county-level observations from each state where a crop is grown and emerging pest populations provides a detailed set of observations to assess the impact of a changing climate on agriculture. Continued refinement of tools to assess climate impacts on agriculture will provide guidance on strategies to adapt to climate change. [ABSTRACT FROM AUTHOR]

The global food system is increasingly interconnected and under pressure to support growing demand. At the same time, crop production is facing new and uncertain impacts from climate change. To date, understanding how downstream supply chain actors, such as commodity traders, are exposed to climate change risks has been difficult due to a lack of high-resolution climate and trade data. However, the recent availability of supply chain data linking subnational production to downstream actors, and gridded projections of crop yield under climate change, allows us to assess individual commodity trader exposure to long-term climate change risk. We apply such an analysis to soy production in Brazil, the world's largest soy exporter. Whilst uncertainty across crop models' yield projections means it remains difficult to accurately predict how production across the region will be affected by climate change, we demonstrate that the risk exposure of trading actors differs substantially due to the heterogeneity in their sourcing. Our study offers a first attempt to analyze subnational climate risk to individual trading actors operating across an entire production landscape, leading to more precise risk exposure analysis. With sufficient subnational data, this method can be applied to any crop and country combination, and in the context of wider food security issues, it will be pertinent to apply these methods across other production systems and downstream actors in the food system. [ABSTRACT FROM AUTHOR]

Coastal farmers are the first group of people who feel climate-related calamities most severely, such as sea-level rise, salinity intrusion, coastal flooding, tidal surges and tropical cyclones. They are operating agricultural activities under these climatic conditions that affect farm productivity. This study explores farmer perceptions of changes in farm productivity and perceptions of causes of decreased farm productivity (if any) over the past 10 years compared with more than 10 years back. We partitioned the causes of decreased farm productivity into climatic and non-climatic based on the primary data collected through household survey in ten coastal subdistricts along the coast of the Bay of Bengal. We visited 381 households during September–October 2018 using a pre-tested structured interview schedule. Average monetary farm productivity in the study area was 1.98. A small proportion (11%) of the sampled farmers mentioned that farm productivity had decreased over the past years. A majority (64%) of them believed that climate change was responsible for such decreases in farm productivity. The farmers who thought that climate change was causing the decreased farm productivity were characterized by greater education, more awareness of climate change, less communication with extension agents, stronger belief in decreased cyclone and salinity, and weaker belief in decreased flood. The farmers perceived that dry period salinity, flood and coastal inundations were the major products of climate change to adversely affect crop productivity. Since agricultural adaptation to climate change requires clear understanding of the climatic impacts on farm productivity, and more than one-third of the farmers failed to identify climatic impacts on decreased farm productivity, their improvement of climate change awareness is essential. Extension organizations and other agents should promote updated climate knowledge among farmers to make them more aware of climate change issues, so that they can adapt to climate change through their agricultural activities. [ABSTRACT FROM AUTHOR]

The potential impacts of climate change on wheat were assessed for Kulmsa area in central highlands of Ethiopia using the Agricultural Production Systems sIMulator (APSIM)—wheat model. The objectives were to (i) evaluate the performance of wheat under increased temperatures with or without changes in rainfall and carbon dioxide (CO2) levels and (ii) assess the response of different wheat cultivars to projected future climates under improved management practices (optimal nitrogen rate, planting date, and density) (IMPs). The model was first calibrated and used to identify ranges of IMPs. Then, the model was used to (i) conduct sensitivity analysis of wheat in response to assumed elevated temperature (T), with and without change in rainfall and CO2 level, and to (ii) evaluate average effect of future worst-case climate change scenarios as predicted by an ensemble of three global climate models (GCM) under highest Representative Concentration Pathways (RCP8.5) for three future time frames, NF (2010–2039), MC (2040–2069), and EC (2070–2099). The simulation was evaluated for three wheat cultivars ("early", "medium", and "late") relative to their corresponding baseline values under the selected IMPs. The baseline climate was represented by the long-term (1980–2009) dataset and CO2 of 360 μmol/mol. Results showed that increased temperature above 4 °C alone had strong negative impacts on yields under the IMPs when CO2 staying constant at the baseline level. In contrast, climate change simulations with GCM projections under IMPs and elevated CO2 effect showed that wheat yield remained unchanged (− 0.4 to + 9%) for all three genotypes. This suggests that the IMPs and elevated CO2 were able to reduce the negative effect of elevated T on wheat yield as T stress did not go beyond optimal T range for wheat. Overall, climate change may not reduce wheat production in the climate of the location of study in the near future, midcentury, or end century. [ABSTRACT FROM AUTHOR]

Reliable projections of crop production are an essential tool for the design of feasible policy plans to tackle food security and land allocation, and an accurate characterization of the long-run trend in crop yield is the key ingredient in such projections. We provide several contributions adding to our current understanding of the impact of climatic factors on crop yield. First of all, reflecting the complexity of agricultural systems and the time required for any change to diffuse, we show that crop yield in Europe has historically been characterized by a stochastic trend rather than the deterministic specifications normally used in the literature. Secondly, we found that, contrary to previous studies, the trend in crop yield has slowly changed across time rather than being affected by a single abrupt permanent change. Thirdly, we provide strong evidence that climatic factors have played a major role in shaping the long-run trajectory of crop yield over the decades, by influencing both the size and the statistical nature of the trend. In other words, climatic factors are important not only for the year-to-year fluctuations in crop yield but also for its path in the long-run. Finally, we find that, for most countries in this study, the trend in temperature is responsible for a reduction in the long-run growth rate of yield in wheat, whereas a small gain is produced in maize, except for Southern European countries. [ABSTRACT FROM AUTHOR]

Though climate events pose increasing challenges for crop and animal production in Africa, most climate adaptation studies focus on staple food crops. Few studies have examined climate adaptation for livestock with even fewer looking at small animals such as poultry. Heat stress associated with climate change is a severe challenge to poultry farmers due to its negative effect on chicken growth and productivity. As poultry plays an important food security role across Africa (being a source of livelihood and an important source of animal protein), understanding how farmers deal with the realities of poultry production due to climate change is critical. This study explores the level and determinants of the adoption of climate change adaptation strategies among poultry farmers in Nigeria. A multivariate probit analysis (which allows for the possibility that the decision to adopt various practices are jointly made) reveals that while poultry farmers are adapting to climate change, there is a clear heterogeneity of adaptation strategies at different production scales. Small farms tend to invest in traditional strategies such as the stocking of local breeds while medium and large farms adopt modern technologies such as air and water ventilation as well as the use of low energy bulbs that emit less heat. Our study finds that farmers who have experienced heat-related losses are more likely to adopt modern practices and more likely to adopt multiple adaptation strategies concurrently. [ABSTRACT FROM AUTHOR]

Small-scale farmers are highly threatened by climate change. Experts often base their interventions to support farmers to adapt to climate change on their own perception of farmers' livelihood risks. However, if differences in risk perception between farmers and experts exist, these interventions might fail. Thus, for effective design and implementation of adaptation strategies for farmers, it is necessary to understand farmers' perception and how it influences their decision-making. We analyze farmers' and experts' systemic view on climate change threats in relation to other agricultural livelihood risks and assess the differences between their perceptions. For Cauca, Colombia, we found that experts and farmers perceived climate-related and other livelihood risks differently. While farmers' perceived risks were a failure in crop production and lack of access to health and educational services, experts, in contrast, perceived insecurity and the unreliable weather to be the highest risks for farmers. On barriers that prevent farmers from taking action against risks, experts perceived both external factors such as the national policy and internal factors such as the adaptive capacity of farmers to be the main barriers. Farmers ranked the lack of information, especially about weather and climate, as their main barrier to adapt. Effective policies aiming at climate change adaptation need to relate climate change risks to other production risks as farmers often perceive climate change in the context of other risks. Policymakers in climate change need to consider differences in risk perception. [ABSTRACT FROM AUTHOR]

Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021-2060 and far future period 2061-2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment. [ABSTRACT FROM AUTHOR]

Maize (Zea mays) is one of the staple crops of West Africa and is therefore of high importance with regard to future food security. The ability of West Africa to produce enough food is critical as the population is expected to increase well into the twenty-first century. In this study, a process-based crop model is used to project maize yields in Africa for global temperatures 2 K and 4 K above the preindustrial control. This study investigates how yields and crop failure rates are influenced by climate change and the efficacy of adaptation methods to mitigate the effects of climate change. To account for the uncertainties in future climate projections, multiple model runs have been performed at specific warming levels of + 2 K and + 4 K to give a better estimate of future crop yields. Under a warming of + 2 K, the maize yield is projected to reduce by 5.9% with an increase in both mild and severe crop failure rates. Mild and severe crop failures are yields 1 and 1.5 standard deviations below the observed yield. At a warming of + 4 K, the results show a yield reduction of 37% and severe crop failures which previously only occurred once in 19.7 years are expected to happen every 2.5 years. Crops simulated with a resistance to high temperature stress show an increase in yields in all climate conditions compared to unadapted crops; however, they still experience more crop failures than the unadapted crop in the control climate. [ABSTRACT FROM AUTHOR]

Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981-2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (Tmean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to Tmean and positively related to PRE and SSD. The positive sensitivity response to Tmean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date. [ABSTRACT FROM AUTHOR]

Correctly estimating the effect of elevated CO2 (eCO2) on biomass production is paramount for accurately projecting agricultural productivity, global carbon balances and climate changes. Plant physiology suggests that eCO2 should result in a strongly positive CO2 fertilisation effect (CFE) via positive effects on photosynthesis and water use efficiency. However, the CFE in CO2 experiments is often constrained because of other factors of which rainfall pattern is particularly important. Here, we apply a generally applicable, empirically derived relationship between the CFE and an index of seasonal rainfall balance (SRB), to identify how historical and projected future rainfall patterns modify the CFE using 25 native grassland sites in south-eastern (SE) Australia as a test case. We found that historical and projected rainfall produced SRBs that varied widely from year-to-year resulting in a CFE that was only positive in about 40% of years, with no or even negative biomass responses in the remainder of years; a finding that is in marked contrast to other studies that have not taken account of relationships between rainfall seasonality and plant responses to CO2. The dependence of the CFE on SRB also means that using the CFE from a specific eCO2 experiment can be misleading as the result will be heavily influenced by the SRB during the period of experimentation but this problem can be avoided by using a robust general relationship of the kind used in this study. Generalisations of grassland biomass responses to the rising CO2 concentration are contextual in terms of the variability in precipitation seasonality; as such, this provides a new lens by which to view aboveground responses to the rising CO2 concentration and fosters a novel approach for cross-site comparisons among experiments. [ABSTRACT FROM AUTHOR]

Using recent advances in statistical crop yield modelling and a unique dataset consisting of yield time series for Russian regions over the period from 1955 to 2012, the study investigates the potential impact of climate change (CC) on the productivity of the three most important grains. Holding current grain growing areas fixed, the aggregate productivity of the three grains is predicted to decrease by 6.7% in 2046-2065 and increase by 2.6% in 2081-2100 compared to 1971-2000 under the most optimistic representative emission concentration pathway (RCP). Based on the projections for the three other RCPs, the aggregate productivity of the three studied crops is assessed to decrease by 18.0, 7.9 and 26.0% in the medium term and by 31.2, 25.9 and 55.4% by the end of the century. Our results indicate that CC might have a positive effect on winter wheat, spring wheat and spring barley productivity in a number of regions in the Northern and Siberian parts of Russia. However, due to the highly damaging CC impact on grain production in the most productive regions located in the South of the country, the overall impact tends to be negative. Therefore, a shift of agricultural production to the Northern regions of the country could reduce the negative impact of CC on grain production only to a limited extent. More vigorous adaptation measures are required to maintain current grain production volumes in Russia under CC. [ABSTRACT FROM AUTHOR]

Climate change is increasingly affecting rural areas worldwide. The Lower Mekong Basin (LMB) is at particular risk due to heat stress, changing rainfall patterns, rising sea levels, and more frequent and extreme climatic events. It is imperative that local-level adaptation plans are developed in a manner that builds resilience to these growing threats. Strategies for developing adaptation plans tend to comprise predominantly science-led or predominantly community-led processes. This study examines an approach that balances inputs from both processes in characterizing community vulnerability as a component of the adaptation planning workflow. Evaluation sites are located within four distinct sub-regions of the LMB: the Vietnam Mekong Delta, the Annamite Mountains of Lao PDR, the Cambodia central lowlands, and the mid-elevation forests of northern Thailand. Our results indicate that by merging science-based data with community-level perspective, knowledge gaps from both sides are filled and a more comprehensive understanding of vulnerability is factored into adaptation planning. [ABSTRACT FROM AUTHOR]

Crop production in the Central High Plains is at an all-time high due to increased demand for biofuels, food, and animal products. Despite the need to produce more food by mid-century to meet expected population growth, under current management and genetics, crop production is likely to plateau or decline in the Central High Plains due to groundwater withdrawal at rates that greatly exceed recharge to the aquifer. The Central High Plains has experienced a consistent decline in groundwater storage due to groundwater withdrawal for irrigation greatly exceeding natural recharge. In this heavily irrigated region, water is essential to maintain yields and economic stability. Here, we evaluate how current trends in irrigation demand may impact groundwater depletion and quantify the impacts of these changes on crop yield and production through to 2099 using the well-established System Approach to Land Use Sustainability (SALUS) crop model. The results show that status quo groundwater management will likely reduce irrigated corn acreage by ~60% and wheat acreage by ~50%. This widespread forced shift to dryland farming, coupled with the likely effects of climate change, will contribute to overall changes in crop production. Taking into account both changes in yield and available irrigated acreage, corn production would decrease by approximately 60%, while production of wheat would remain fairly steady with a slight increase of about 2%. [ABSTRACT FROM AUTHOR]

We use new household level data from Niger and regression analysis to study the role of drought perception and human capital-including empowerment-in climate change adaptation through the digging of zaї pits and effects of these pits on agricultural productivity. We find that selection of households into adoption of zaï pits is influenced by the perception that the frequency of droughts has increased. More educated, experienced, and empowered households are also more likely to have put in place zaï pits. Accounting for endogeneity of adoption, zaї pits are found to significantly increase cereal yields. Our counterfactual analysis reveals that even though all households would benefit from adoption of zai pits, the effect would be significantly larger for households that did not adopt if they had adopted. For the latter group, empowerment in particular is associated with significantly higher yields. [ABSTRACT FROM AUTHOR]

Trajectories of policy-driven transient temperatures are reported here for four different maximum temperature targets through 2100 and a 'no-policy' baseline because it is they, and their associated manifestations in other impact and risk dimensions, that natural and human and natural systems see in real time as their common future unfolds. It follows that it is they that inform both the reactive and (for human systems) anticipatory responses that embedded decision-makers would contemplate in the future. Median pathways as well as 5th and 95th percentile alternatives for each set of scenarios are reported in decadal increments from 2010 through 2100. Two illustrations (agricultural yields and Intergovernmental Panel on Climate Change 'reasons for concern') are presented to provide provocative context within which to begin to see their potential value across a wide range of applications. [ABSTRACT FROM AUTHOR]

Climate change has been projected to significantly affect agricultural productivity and hence food availability in the coming decades. The uncertainty associated with projecting climate change impacts is a barrier to agricultural adaptation. Despite uncertainty quantification becoming more prominent in impact studies, the thorough quantification of more than one uncertainty source is not commonly exercised. This work focuses on Indian groundnut and uses the General Large Area Model for annual crops (GLAM) to investigate the response of groundnut under future climate scenarios, develop a genotypic adaptation strategy, and quantify the main uncertainty sources. Results suggest that despite large uncertainty in yield projections (to which crop- and climate-related sources contribute 46 and 54 %, respectively) no-regret strategies are possible for Indian groundnut. Benefits from genotypic adaptation were robust towards the choice of climate model, crop model parameters and bias-correction methods. Groundnut breeding for 2030 climates should be oriented toward increasing maximum photosynthetic rates, total assimilate partitioned to seeds, and, where enough soil moisture is available, also maximum transpiration rates. No benefit from enhanced heat stress tolerance was observed, though this trait may become important as warming intensifies. Managing yield variability remains a challenge for groundnut, suggesting that an integral approach to crop adaptation that includes year-to-year coping strategies as well as improvements in crop management is needed across all India. [ABSTRACT FROM AUTHOR]

Research aiming to reduce the vulnerability of agricultural systems to climate variability and change requires practical appraisal of their climatic exposure. We propose a method to map local climatic conditions over a given period to a set of productivity and management-related indicators that are specific to grassland-based livestock systems. Our method based on a reference system balances herbage production and feed requirements over a long period (≥ 30 years) and provides boundaries for productivity-defined seasons and indicators for surplus or shortage of herbage at seasonal and annual scales. This exposure-assessment method was applied to five climatically contrasting locations in south-western France. The trends and variability of the exposure indicators were analysed for past (1980-2010) and future (2035-2065) periods, considering the A1B scenario of the IPCC. Despite high year-to-year variability and the heterogeneity of the climatic situations studied, we show that climate change can modify the boundaries of productivity-defined seasons and seasonal herbage surplus or shortage. Moreover, the exposure indicators succeed in detecting climate-induced changes and distinguishing situations where a classical exposure indicator, such as annual forage production, could not. The exposure indicators highlight the forage productivity and the timing of production associated with local climatic conditions. These features fit the temporal scale at which farmers consider farm management and are highly suitable for identifying adaptation strategies that reduce the vulnerability of grassland-based livestock systems. [ABSTRACT FROM AUTHOR]

Nearly all of Ethiopia's agriculture is dependent on rainfall, particularly the amount and seasonal occurrence. Future climate change predictions agree that changes in rainfall, temperature, and seasonality will impact Ethiopia with dramatic consequences. When, where, and how these changes will transpire has not been adequately addressed. The objective of our study was to model how projected climate change scenarios will spatially and temporally impact cereal production, a dietary staple for millions of Ethiopians. We used Maxent software fit with crop data collected from household surveys and bioclimatic variables from the WorldClim database to develop spatially explicit models of crop production in Ethiopia. Our results were extrapolated to three climate change projections (i.e., Canadian Centre for Climate Modeling and Analysis, Hadley Centre Coupled Model v3, and Commonwealth Scientific and Industrial Research Organization), each having two emission scenarios. Model evaluations indicated that our results had strong predictability for all four cereal crops with area under the curve values of 0.79, 0.81, 0.79, and 0.83 for teff, maize, sorghum, and barley, respectively. As expected, bioclimatic variables related to rainfall were the greatest predictors for all four cereal crops. All models showed similar decreasing spatial trends in cereal production. In addition, there were geographic shifts in land suitability which need to be accounted for when assessing overall vulnerability to climate change. The ability to adapt to climate change will be critical for Ethiopia's agricultural system and food security. Spatially explicit models will be vital for developing early warning systems, adaptive strategies, and policy to minimize the negative impacts of climate change on food production. [ABSTRACT FROM AUTHOR]

We investigate the effect of climate change on crop productivity in Africa using satellite derived data on land use and net primary productivity (NPP) at a small river basin scale, distinguishing between the impact of local and upper-catchment weather. Regression results show that both of these are determining factors of local cropland productivity. These estimates are then combined with climate change predictions obtained from two general circulation models (GCMs) under two greenhouse gas emissions (GHG) assumptions to evaluate the impact of climate change by 2100. For some scenarios significant decreases are predicted over the northern and southern parts of Africa. [ABSTRACT FROM AUTHOR]

A regional nuclear war between India and Pakistan with a 5 Tg black carbon injection into the upper troposphere would produce significant climate changes for a decade, including cooling, reduction of solar radiation, and reduction of precipitation, which are all important factors controlling agricultural productivity. We used the Decision Support System for Agrotechnology Transfer agricultural simulation model to simulate regional nuclear war impacts on rice yield in 24 provinces in China. We first evaluated the model by forcing it with daily weather data and management practices for the period 1980-2008 for 24 provinces in China, and compared the results to observations of rice yields in China. Then we perturbed observed weather data using climate anomalies for a 10-year period from a nuclear war simulation. We perturbed each year of the 30-year climate record with anomalies from each year of the 10-year nuclear war simulations for different regions in China. We found that rice production would decline by an average of 21 % for the first 4 years after soot injection, and would slowly recover in the following years. For the next 6 years, the reduction in rice production was about 10 %. Different regions responded differently to climate changes from nuclear war. Rice production in northern China was damaged severely, while regions along the south and east coasts showed a positive response to regional nuclear war. Although we might try to adapt to a perturbed climate by enhancing rice planting activity in southern and eastern China or increasing fertilizer usage, both methods have severe limitations. The best solution to avoid nuclear war impacts on agriculture is to avoid nuclear war, and this can only be guaranteed with a nuclear-weapon-free world. [ABSTRACT FROM AUTHOR]

A rapid change in climate patterns potentially driven by global warming is considered to be greatest threats to agriculture. However, little is known about how the change in climate concretely affects agricultural production especially in Nepal with respect to seasons and regions of different altitudes. To examine this issue, we seek to empirically identify the impact of climatic variation on agricultural yield and its variability by utilizing the data of rice, wheat and climate variables in the central region of Nepal. The main focus is on whether the impacts vary across seasons, altitudes and the types of crops. For this purpose, we employ a stochastic production function approach by controlling a novel set of season-wise climatic and geographical variables. The result shows that an increase in the variance of both temperature and rainfall has adverse effects on crop productions in general. On the other hand, a change in the mean levels of the temperature and rainfall induces heterogeneous impacts, which can be considered beneficial, harmful or negligible, depending on the altitudes and the kinds of crops. These results imply that adaptation strategies must be tailor-made in Nepalese agriculture, considering growing seasons, altitudes and the types of crops. [ABSTRACT FROM AUTHOR]

The susceptibility of agriculture to changing environmental conditions is arguably the most dangerous short-term consequence of climate change, and predictions on the geography of changes will be useful for implementing mitigation strategies. Ecological niche modeling (ENM) is a technique used to relate presence records of species to environmental variables. By extrapolation, ENM maps the suitability of a landscape for the species in question. Recently, ENM was successfully applied to predict the geographic distribution of agriculture. Using climate and soil conditions as predictor variables, agricultural suitability was mapped across the Old World. Here, I present analogous ENM-based maps of the suitability for agriculture under climate change scenarios for the year 2050. Deviations of predicted scenarios from a current conditions model were analyzed by (1) comparing relative average change across regions, and (2) by relating country-wide changes to the data indicative of the wealth of nations. The findings indicate that different regions vary considerably in whether they win or lose in agricultural suitability, even if average change across the entire study region is small. A positive relationship between the wealth of nations and change in agriculture conditions was found, but variability around this trend was high. Parts of Africa, Europe and southern and eastern Asia were predicted to be particularly negatively affected, while north-eastern Europe, among other regions, can expect more favorable conditions for agriculture. The results are presented as an independent 'second opinion' to previously published, more complex forecasts on agricultural productivity and food supply variability due to climatic change, which were based on fitting environmental variables to yield statistics. [ABSTRACT FROM AUTHOR]

In the current review we wish to draw attention to an additional aspect of invasive species and climate change, that of agricultural productivity and food security. We recognize that at present, such a review remains, in part, speculative, and more illustrative than definitive. However, recent events on the global stage, particularly in regard to the number of food riots that occurred during 2008, even at a time of record harvests, have prompted additional interest in those factors, including invasive species, which could, through climatic uncertainty, alter food production. To that end, as agricultural scientists, we wish to begin an initial evaluation of key questions related to food production and climate change including: how vulnerable is agriculture to invasive species?; are current pest management strategies sufficient to control invasive outbreaks in the future?; what are the knowledge gaps?; can we provide initial recommendations for scientists, land managers and policy makers in regard to available resources? Our overall goals are to begin a synthesis of potential impacts on productivity, to identify seminal research areas that can be addressed in future research, and to provide the scientific basis to allow agronomists and land managers to formulate mitigation and adaptation options regarding invasive species and climate change as a means to maintain food security. [ABSTRACT FROM AUTHOR]

A simulation study was carried out to assess the potential sensitivity of wheat growth and water balance components to likely climate change scenarios at Wagga Wagga, NSW, Australia. Specific processes considered include crop development, growth rate, grain yield, water use efficiency, evapotranspiration, runoff and deep drainage. Individual impacts of changes in temperature, rainfall and CO2 concentration ([CO2]) and the combined impacts of these three variables were analysed for 2050 ([CO2] = 570 ppm, T +2.3°C, P −7%) and 2070 ([CO2] = 720 ppm, T +3.8°C, P −10%) conditions. Two different rainfall change scenarios (changes in rainfall intensity or rainfall frequency) were used to modify historical rainfall data. The Agricultural Production Systems Simulator (APSIM) was used to simulate the growth and water balance processes for a 117 year period of baseline, 2050 and 2070 climatic conditions. The results showed that wheat yield reduction caused by 1°C increase in temperature and 10% decrease in rainfall could be compensated by a 266 ppm increase in [CO2] assuming no interactions between the individual effects. Temperature increase had little impact on long-term average water balance, while [CO2] increase reduced evapotranspiration and increased deep drainage. Length of the growing season of wheat decreased 22 days in 2050 and 35 days in 2070 conditions as a consequence of 2.3°C and 3.8°C increase in temperature respectively. Yield in 2050 was approximately 1% higher than the simulated baseline yield of 4,462 kg ha − 1, but it was 6% lower in 2070. An early maturing cultivar (Hartog) was more sensitive in terms of yield response to temperature increase, while a mid-maturing cultivar (Janz) was more sensitive to rainfall reduction. Janz could benefit more from increase in CO2 concentration. Rainfall reduction across all rainfall events would have a greater negative impact on wheat yield and WUE than if only smaller rainfall events reduced in magnitude, even given the same total decrease in annual rainfall. The greater the reduction in rainfall, the larger was the difference. The increase in temperature increased the difference of impact between the two rainfall change scenarios while increase in [CO2] reduced the difference. [ABSTRACT FROM AUTHOR]

A well tested agricultural systems model was used together with 114 years of historical climate data to study the performance of a dryland wheat–fallow system as impacted by climate variations and nitrogen input levels in southeast Australia, and to investigate the value of: (1) historical climate knowledge, (2) a perfect climate forecast, and (3) various forecasts of targeted variables. The potential value of historical climate records increases exponentially with the number of years of data. In order to confidently quantify the long term optimal nitrogen application rate at the study site at least 30 years of climate data are required. For nitrogen management only, the potential value of a perfect climate forecast is about $54/ha/year with a reduction of excess nitrogen application of 20 kg N/ha/year. The value of an ENSO based forecast system is $2/ha/year. Perfect forecasting of three or six categories of growing season rainfall would have a value of $10–12/ha/year. Perfect forecasts of three or six categories of simulated crop yield would bring about $33–34/ha/year. Choosing integrated variables as a forecasting target, for example crop yield derived from agricultural modelling, has the potential to significantly increase the value of forecasts. [ABSTRACT FROM AUTHOR]

Abstract A methodology is described for estimating robustness of recommended farm plans under climate change while maintaining a meaningful representation of the underlying farm system. Monte Carlo Simulation (MCS) of crop yield data is used in conjunction with a fully specified farm-level model and output from a field worktime model. Estimates of farm net margin, enterprise mix (choice and area of enterprises), labour, machinery, storage and animal housing under mean crop yields and field worktimes for current (2000s) and 2050s conditions are generated. MCS is used to estimate the effect of crop yield variation on farm profitability and enterprise mix for the same periods by running the farm-level model with no constraints and running it constrained to the mean data plan. Estimates of robustness, measured as the percentage difference and the probability of exceeding the mean farm net-margin, were calculated from the outputs from these runs. For three representative farm types, mean farm net margin increased; however changes in robustness as shown by percentage difference in farm net margin depended on farm type while the probability of exceeding the mean plan net-margin decreased by 2050 indicating an increase in robustness. The most robust farm type had a diversified mix of enterprises and required no additional fixed resources by the 2050s. The least robust farm type was in a marginal location and mean plan recommendations for the 2050s required additional investment in fixed resources, particularly irrigation. It is concluded that the information provided by the methodology would be particularly useful to farmers: where mean data plans are not robust, MCS results could be used with financial planning techniques to minimise the impact of variability, rather than using high cost inputs to reduce variability per se. [ABSTRACT FROM AUTHOR]

We examined the impacts on U.S. agriculture of transient climate change as simulated by 2 global general circulation models focusing on the decades of the 2030s and 2090s. We examined historical shifts in the location of crops and trends in the variability of U.S. average crop yields, finding that non-climatic forces have likely dominated the north and westward movement of crops and the trends in yield variability. For the simulated future climates we considered impacts on crops, grazing and pasture, livestock, pesticide use, irrigation water supply and demand, and the sensitivity to international trade assumptions, finding that the aggregate of these effects were positive for the U.S. consumer but negative, due to declining crop prices, for producers. We examined the effects of potential changes in El Niño/Southern Oscillation (ENSO) and impacts on yield variability of changes in mean climate conditions. Increased losses occurred with ENSO intensity and frequency increases that could not be completely offset even if the events could be perfectly forecasted. Effects on yield variability of changes in mean temperatures were mixed. We also considered case study interactions of climate, agriculture, and the environment focusing on climate effects on nutrient loading to the Chesapeake Bay and groundwater depletion of the Edward's Aquifer that provides water for municipalities and agriculture to the San Antonio, Texas area. While only case studies, these results suggest environmental targets such as pumping limits and changes in farm practices to limit nutrient run-off would need to be tightened if current environmental goals were to be achieved under the climate scenarios we examined [ABSTRACT FROM AUTHOR]